Tinder Initiation Messages
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Tinder Initiation Messages
Ben Seefeldt
Department of Computer Science
University of Illinois
Urbana, IL
seefldt2@illinois.edu
ABSTRACT We present our results in the form of a visualization which
In this paper, we explore the use of the social dating smart- surfaces interesting pieces of information gathered from our
phone application ‘Tinder’. We gathered data on over 1200 study.
unique Tinder users using dummy accounts. We analyze
these results to discern meaningful trends in user interac- As tools like Tinder become more common as a courtship
tions, with a particular focus on the ways in which initi- replacement, the cultural norms present on these platforms
ation messages reflect culturally accepted courtship scripts. will be come increasingly important. We hypothesize that
We provide a usefully visualization of these results which can the highly visual nature of Tinder will have a dramatic effect
be used both to intuitively discern our conclusions from the on the types of interactions it facilitates.
data, and also explore the dataset as a whole. Our findings
indicate that among college-aged individuals, our female ac- 2. BACKGROUND AND RELATED WORK
count received dramatically more matches, as well as more
initiation messages. 2.1 Tinder
“Tinder is how people meet. It’s like real life, but better[10].”
1. INTRODUCTION
Tinder is an application for iOS and Android which matches
Tinder is a smartphone application which allows users to
individuals using proximity and images. It is available for
anonymously view images of other users and either like or
free and requires a Facebook account for login. Tinder is
dislike these photos. Matching allows users to message each
a relative newcomer, but has quickly reached acclaim. It
other and potentially meet in person. In popular culture,
recently was awarded TechCrunch’s Best New Startup of
Tinder is commonly associated with hookups. The appli-
2013 award[9].
cation is popular among college aged students and requires
much less buy-in than traditional dating websites. Tinder is
After logging in with a Facebook account, the application
unique it its ‘game-like’ approach to meeting new people.
prompts you to design your profile. By default it will fill
in your photo section with a selection of images from your
Better understanding how individuals act in potentially ro-
Facebook. These photographs are editable, but must be
mantic relationships is an extremely interesting area of re-
pictures of you tagged on Facebook. Users are given one
search. Understanding courtship and gendered scripts re-
primary profile picture and any number of additional sec-
garding initiation are common topics of study in psychology.
ondary pictures. In addition, Tinder allows a user 500 char-
Additionally, much work has been done looking into how
acters to write an “About You” section. Anecdotally, we
computer mediated relationships form, in particular, how
observed this section typically contained information either
they differ from relationships that begin in physical spaces.
about the user’s school (i.e. school name or class standing)
We will examine some of this work in our background sec-
or about the type of relationship they were interested in ini-
tion.
tiating (hookup, friendship, long-term, etc.). It is also worth
noting that for the public played profile, only first names are
We were interested in particular on how success with Tin-
displayed.
der depended upon gender, and whether different genders
and sexual orientations differed in initiation type of mes-
In the settings menu, users able to set their gender, and the
sage content. We believe that interesting insights may be
gender(s) of users whose profiles they are interested in see-
gained about college-aged users usage patterns of this tool.
ing. They are also able to set an age range for other users.
It is worth noting that the ages for users are set from infor-
mation gathered from Facebook. The final search variable
that users can set from this menu is the maximum distance
away they want to match with people. Tinder actively uses
the phone’s GPS to set location and match with users in the
vicinity. This means that if a users travels to different cities
they will be presented with a new pool of potential matches.
The main screen of the application displays a stack of profile
Figure 1: (Left) The main screen of the Tinder application. From this view, we can see the potential match’s
image, and number of shared friends and likes. We can either like or dislike using the buttons on the
bottom. (Right) The detail view. We can see that Sarah Helm (another group member) is a shared friend.
Additionally, we can see the four Facebook pages both users like.
cards. Underneath the stack of cards, there is a red ‘X’, a ground of many of these theories1 , we will present a short
blue ‘i’, and a green heart. On the board of the image, we see summary of several theories as they apply to our research.
three icons indicating, from left to right, number of shared
friends, number of shared likes, and number of additional One major distinction in the literature is the difference be-
images. Selecting the ‘i’ button allows us to see additional tween cues filtered out and cues filtered in. These two per-
information about the user including images, and a list of spectives view computer mediated communication in dra-
shared likes and friends. matically different ways. Cues filtered out maintains that
the limitations of technology stops users from participating
Using the additional two buttons, we are able to either like or in full fledged communication and that there is an inherent
dislike the current profile. This can also be done by swiping limitation to the amount of personal contact that can oc-
the card to either the right or the left, respectively. Once a cur through technologically medicated communication. It
decision has been made, the profile is hidden from view and claims that the lack of additional cues impair communica-
the next profile is displayed. tion.
If both users like each others profiles a match will take place. Conversely, the cues filtered in perspective asserts that users
A short popup will occur for the second user to like, and of technological systems introduce additional cues into the
notifications may be sent to the first party. Mutual matches communication patterns that replace traditional non-spoken
are put into a list that can be accessed from the Tinder cues. In this way, the artifacts of the communication become
menu. For each match, there is a chat window. Messages can another source of information.
be sent and received in a manner similar to text messages.
While addressing this distinction is not the key focus of our
This is the end of Tinder involvement. Past this point, the project, we will prematurely address an interesting piece of
two individuals facilitate all communication. Communica- information that we believe corroborates the cues filtered
tion can be blocked or moved to different forums. in perspective. We found that users of Tinder expect re-
turn messages in a short time period. We received several
messages of dismissal after only a day of waiting. This indi-
cates that users are reinterpreting a slow message response
time as disinterest. Unfortunately, our work did not address
2.2 Previous Work extended communication between Tinder users. We focus
There has been much work done on the topic of dating and
relationship building using technology as a tool for commu- 1
Preliminary Examination Question #1: Dating and Tech-
nication. Thanks to a wonderful paper providing the back- nologically Medicated Communication, Liesel L. Sharabi
exclusively upon the initiation messages. There are assum- Our interest in the use of technologically mediated commu-
ably additional cues that users filter in while using Tinder, nication motivated us to begin a cursory exploration into
and examining serious Tinder users’ chat histories would be communication norms on Tinder. To this end we proposed
a convenient way to do this. several research questions.
In Monica Whitty’s paper, “Cyber-Flirting: An Examina-
tion of Men’s and Women’s Flirting Behaviour Both Offline • How does gender impact the number of matches?
and on the Internet”[12] she finds that men are more likely
than women to initiate contact in chatrooms, a conclusion • How does sexual orientation impact the number of
that we found supported in our work. She additionally states matches?
taht while there are some physical cues that transition into • Do different groups of users rely on different types of
digital spaces, more research is needed. language during initiation messages? (e.g. emoticons,
questions, etc.)
In reference to the potential for online profiles to be curated,
Joseph Walther remarks, “The point here is that the infor-
mation one gives about oneself is more selective, malleable, Tinder provides ample information for the exploration of a
and subject to self- censorship in CMC (computer mediated wide variety more topics including distance and profile bi-
communication) than it is in FtF (face to face) interaction ography, as well as questions concerning user demographics
because only verbal and linguistic cues–those that are most (e.g. race, age). Due to limitations of time and resources,
at our discretion and control–are our displays”[11]. Walther we chose to focus on questions of initiation. While interper-
comments on the potential for users to provide obfuscated sonal communication is certainly a compelling aspect to the
or curated views of themselves to others. Views that may platform, it is difficult to explore without an easily available
be potentially untruthful and lead to disappointment. backlog of chat records from a variety of sources.
This concept is also explored by Ellison, who presents a
framework for understanding the implicit promises that are
3.1 Setup
Initially we had intended on creating four profiles to use
made by users through their profile information[1] as well as
for our experiment, Two male accounts and two female ac-
Hancock, who presents a study on the perceived accuracy of
counts. Tinder provides an option to select which gender
dating profile images[4]. As Tinder allows users to create a
you are interested. We intended to cover the four possibili-
highly idealized portrait of themselves for public consump-
ties of gender combinations allowed; male for male, male for
tion, we believe it is the case that this type of deception
female, female for female, and female for male. However,
occurs on a frequent basis, and while it is not the focus of
we ran into significant difficulties creating the requisite ac-
our research topic, it is an interesting area that may warrant
counts. Tinder necessitates a Facebook profile page for login.
additional research.
Both Facebook and Tinder rely on text message verification
for identity. We were unable to create spoof accounts that
Testing the number of responses users receive based on rela-
could be used for this experiment.
tive profile attractiveness is address by Taylor, Fiore, Mendel-
sohn and Cheshire who find that there is indeed evidence of
Due to this limitation we used a group member’s personal
users selection based on perceived physical attractiveness[8].
accounts.2 Rather than complete the experiment using the
They remark that the degree of matching may depend on
four profiles both male and female accounts, we chose to
the stage of the dating process. Further Tinder research
select interest in both males and females for both accounts.
could focus on the use of attractiveness during the decision
to match, initiation, or continued conversation.
Our original intent in creating new Facebook profiles was
to be able to control completely for Facebook likes and dis-
played first name. While this was not possible due to using
3. QUESTIONS AND METHODOLOGY pre-existing personal accounts, using the site of likes that
Tinder is a unique and easily available forum for users to the male and female profiles already had led to some inter-
interact in a potentially romantic way. It differs dramat- esting initiation messages that we will discuss in the results
ically from mainstream dating websites such as OKCupid section of our paper.
or Match.com in that it does not attempt to define a re-
lationship between two users, and is primarily based off of The public information for the tinder profiles consists of two
visual cues. In many ways, it could be said the interaction pictures each, the gender of the user, their age, a short bio,
paradigm favored on Tinder is stylistically similar to that of distance away, and common Facebook likes.
a singles bar.
For the profile images, we used images provided by Clare
In particular, we found Tinder a compelling platform be- Curtis’s sister and sister’s friend who currently attend un-
cause of how common the application is among college aged dergrad in Texas. We did this to avoid recognition. Prior
users[2]. Being positioned at a large university with a sig- work backs up the fact that attractiveness of profile images
nificant student-aged populated gave us easy access to an 2
ample pool of potential Tinder users. While the number of Note that we use used my (Ben Seefeldt) and my fiancée’s
(Kristen Lundberg) accounts. We received permission to
Tinder users in the wider Champaign-Urbana area is not use this data from both individuals and ensured that no
public knowledge, with daily downloads around 20,000, we personal information would be compromised. We will refer
imagine the number is fairly high[3]. to the accounts as male and female from this point forward.
Figure 2: The public facing profiles for the male and female accounts.
is a major factor in the number of responses a user will re- matches to occur from a single benchmark. Secondly, Tinder
ceive on an online dating website. We attempted to pick displays an additional transition page if you select someone
profile images that were of comparable levels of attractive- who has already selected you. By selecting everyone we
ness. While this is no doubt a subjective judgement, rating would use for our experiment before our profile had been
the attractiveness of our profiles was not the intention of this public for any length of time we avoid this annoyance.
project, and we believe the images are comparable enough
for a pilot study such as this. After selection of initial matches we waited three days to
download the data from our devices. This allowed time for a
The bio field for both profiles was set to, “UIUC. Ready sizeable body of users to match with us. While it would have
for end of the year fun.” This was chosen as representative been possible for us to wait longer, we recieved a significant
of a set of profiles we had examined before beginning the number of results, and the number of results per hour began
experiment. It was intentionally chosen as slightly leading to drop off after this point.
in order to prompt responses.
For data collection, we were able to directly access the SQLite3
database that is used by the iPhone version of the applica-
3.2 Data Collection tion. On a jailbroken iPhone, it is simply a matter of locat-
After our accounts were created we immediately began data ing the application data folder and downloading the data to
collection. As stated above matches begin to occur after a computer. Once acquired, the data can be explored using
you swipe someone to the right. On Sunday, April 27th at basic SQL queries.
2pm we began to mark people as potential matches on both
accounts. We utilized two devices and completed the same
actions concurrently. We alternated between 30 likes and 1 4. DATA ANALYSIS
dislike. This was in order to avoid being classified as a bot The data analysis we did was largely manual observation.
by Tinder. Over the course of two hour we liked 2020 profiles While there were a large number of messages sent, there were
on each account. Unfortunately, as we selected both same not so many as to stop us from looking through all entries.
sex and opposite sex partners for both accounts, there was While it would have been possible to extract several more
no readily available way to measure the overall number of features from the dataset, it decided it would be best to focus
people we selected. We will present the number of matches our visualization on several highly salient, and potentially
we have, but it’s important to keep this separate from the interesting data features.
number of people we selected as potential matches.
We observed a dramatically larger number of matches from
We opted to select potential matches as a single batch for men to our female account. Below are the counts of the
two reasons. First, it allowed us to observe how long it takes number of matches and the number of accounts who initiated
(in parenthesis). For the number of question marks and the number of emoti-
cons, we wanted to display the percentage of messages in
a given grouping which exhibited that trait. Inspired by
From the way in which our initial visualization divided the space
F M into quadrants, we decided to use a four-point star graph for
F 23(6) 1011(429) visualizing these two pieces of information.
To
M 173(6) 144(66)
This dramatic difference became a major part of our visual-
ization.
5. VISUALIZATION
Having explored our data, we determined that one of the
most salient features of the data set was the raw counts of
people who matched, and those who responded. In particu-
lar, comparing these numbers for all of the different gender
configurations. We wanted to make dramatically apparent
the large number of responses received from men by the fe-
male account.
Another key visual we were interested in displaying was
the photos from each user. Tinder is a startlingly visual
Figure 5: The star charts for the measurements of
medium. Very little textual information is provided in the
question marks and emoticons.
interface. The application encourages users to focus exclu-
sively on the physical attractiveness of a potential partner.
We wanted this same focus to be evident in our visualization.
Star graphs have the benefit of being visually stimulating
Fortunately, the data we collected included all of the profile
and an easy way to compare a variable number of data points
images of users. We decided to use thumbnail images as the
in a more dynamic way than a simple bar chart. Addition-
building blocks of our major visualization. Additionally, we
ally, by using a four-point design, we are able to match the
decided that on mouse over of these images we would popup
quadrants of the star to the quadrant layout used in the
a larger box showing the name of the match with a larger
initial visualization. This gives the visualization a cohesive
image. This was meant to evoke the look of the Tinder
visual feel.
application.
For both pieces of information, we decided to use a percent-
Tinder is also highly gender based. The users gender, as
age of messages rather than raw counts. This allows users,
well as the genders of the users that they match with are a
for example, to easily see the percent of messages with ques-
highly salient feature. The different number of matches and
tion marks for a given demographic group. Percentages give
messages from different genders was one of the most inter-
the benefit of being easily comparable. Using raw counts we
esting parts of the data that we wanted to surface. Indeed,
find that the larger categories dominate, and no additional
all of the visualizations that we settled on for our project
information is gained.
involved the gender split between the two accounts.
In order to facilitate user understanding of our visualiza- 5.2 Message Length
tion, we relied on culturally significant blue and pink colors. The final piece of information we were interested in surfacing
While it is no doubt the case that these colors exhibit a was the message lengths. We found, anecdotally when ex-
strong gender bias which is an over generalization, they can amining the data that men who were propositioning women
serve as strong visual markers which are difficult to misin- were much more likely to have longer messages. Many times
terpret. this corresponded to a more in depth question or state-
ment about likes and dislikes. Correspondingly, we found
In addition to visualizing the number of responses and ini- that when men were propositioning other men, the mes-
tiations we received, we were interested in showing three sages tended to much shorting in length. One or two word
additional features: initiations were fairly common.
To surface this information, we decided upon a histogram.
1. Number of questions asked, as evidenced by question While this forces a deviation from the quadrant layout used
marks. in the earlier sections, we feel that it more accurately dis-
plays the information. We decided that using the raw counts
2. Number of emoticons used. of messages of certain lengths was the best way to go about
presenting the information. Because of this, we had dramat-
3. Length of initiation message.
ically less data about messages sent from women. Because
there was less information fitting this profile, we decided
5.1 Question Marks and Emoticons to focus on the information about messages sent from men.
Figure 3: A full view of the entire visualization Figure 4: The visualization of the profile images.
I never know what to open with, so can we just assume
I said something really awesome and clever that makes
you wanna message me back lol I’m Clayton btw :)
Would you rather be irresistably atttacted to grapefruits
for the rest of your life or have an orgasm every time
you eat a brownie?
Hey you seem really cool, you like first aid kit and bon
iver. Also your glasses are awesome. What’s up
On a scale of 1 to 10, how do you think the U.S. gov
is handling Cliven Bundy and the Nevada land grant?
Btw what does end of the year fun mean? Like a pizza
party? Cause I fuckin love pizza parties
We found that questions were fairly common, as were in-
quiries into common listed likes. We believe this occurs be-
cause as the expected initiator, straight men are expected
to propel a conversation forward. This results in a type of
conversation competition in forums like Tinder. Users must
differentiate themselves by making interesting conversation.
We hypothesize that this does not occur as markedly rela-
tionships between men. The more relaxed initiation message
seem to indicate less competition occurring in the conversa-
Figure 6: Historgram displaying the number of mes- tional space.
sages of certain lengths received by either the female
(top) or male (bottom) accounts. Looking at the same sex interactions observed, existing liter-
ature indicates that among gay men physical attractiveness
is an important marker for partner selection[7]. Unfortu-
Using a histogram mirrored over the x-axis of our visualiza- nately, the limited nature of our results. We had only a sin-
tion allowed us to do this. To integrate the small amount of gle male profile, whose images were intentionally chosen to
female information, we decided to use a stacked bar graph be of average attractiveness. While the cited research arti-
layout. Typically this type of layout is difficult to under- cle in mainly concerned with repeat dating in the real-world,
stand and can many times obfuscate a true comparison of it has potential implications for digital relationship forma-
the data. However, because we had such dramatically differ- tion as well. Future work could be completed using male
ent amounts of data in the two groups, we felt this allowed profiles of different attractiveness. One would hypothesize
us to present the female information, while focusing on mes- that there is a difference between the number of initiation
sages from men. messages.
6. DISCUSSION 7. CONCLUSION
The most striking thing about our results, is how easily they
The success of this simple experiment bodes well for future
fit into accepted social scripts. Social research indicates that
research. There are many possible avenues to explore. Look-
men are, and continue to be the initiators of sexual relation-
ing at the data we gathered, there are several pieces of infor-
ships in a dating situation[6]. While research indicates that
mation we did not explore in detail. For example, it would
female initiation is becoming more common, and accept-
be interesting to look at the volume of responses received
able, our results indicate that in the context of Tinder, it
during different times of the day. Are night messages more
is much less common[5]. Our results indicate that the com-
common? We also have information regarding distance. It
monly accepted practice on Tinder is for men to initiate. In
may be interesting to see if users are more or less likely to
particular, in opposite sex interactions, female initiation is
respond if they are further away. There are many experi-
extremely limited. Comparatively, straight men are much
ments that could be run if researchers had access to more
more likely to both match and initiate.
Tinder accounts. It would be interesting to look into similar
profiles differing only in the attractiveness of the individ-
We note that in addition to number of matches and initia-
ual in the images. It would also be possible to vary the
tions, straight men are more likely to send longer messages
background/posing of the image or the race of the individ-
than gay men. This corresponded to the fact that many
ual. There are many factors that may effect the number of
messages from men to men were simple greetings. (”Hey”,
matches and initiations a user will receive.
”Hi”, ”What’s up?”, etc.) By comparison, many messages
from men to women were longer messages such as:
The clear conclusion from the work we have done is that if
you are interested in using Tinder to meet many new peo-
Hello, so what’s your story? Or an easier question, ple and go on dates, you’ll have the most luck if you are a
what was your favorite place to hike? straight female.In terms of conclusions regarding social scripts surrounding internet. Behaviour Change, 21(02):115–126, 2004.
dating, we observe that many users rely on traditional gen-
der roles when it comes to initiation particularly in straight
relationships. Men are commonly the initiator of contact.
We also notice that straight men are more likely to send
longer messages of initiation and ask more questions.
Additionally, we observe a large number of men initiating
with our male account. Unlike the male/female case, there
is not an obvious socially mediated rule concerning initiation
order.
Tinder provides an excellent platform for social research.
As similar platforms emerge and become more ubiquitous,
there will undoubtedly be more research examining how
users work within the constraints of the system to begin
a relationship.
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